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What is Householding in Data Driven Marketing?

Understanding a customer’s household is a critical component of your data driven marketing efforts. Grouping customers together into “family units” is known as householding. An explanation of how this is done and reasons for why it is done is necessary in building your database.

What is a household in data driven marketing?

In its most rudimentary (and naive) form, a household is a group of people with the same last name living at the same address. This definition is based on an outdated 1950s Leave It To Beaver view of the nuclear family. This view is clearly problematic in the real world. Many couples, both wed and unwed, do not share the same last name, for example.

What you’re concerned with as a marketer is identifying domestic arrangements that involve some sort of mutual financial or budgetary decision making. Two college students sharing a dorm room do not have the same budgetary connection as a young married couple planning for their first child. Thus you would not generally be inclined to consider a dorm room a household. The young married couples’ apartment, however, would be.

The nuts and bolts of householding are definitely not simple. If you don’t use an outside service provider for anything else, hire one to do your householding for you. These service providers have access to data on virtually every household in the country from a wide variety of sources. They can see connections that you would never be able to spot in your own data.

Why the household is so important in data driven marketing

One of the primary reasons for householding is to keep mail costs down. There is typically no reason to send separate marketing offers to every single person in a household. Especially when the offer involves something the household is only going to need once. For example, a family is typically only going to buy one local newspaper subscription.

Generally, one communication per household is a good rule of thumb for your marketing campaigns. This rule is most important for more expensive campaigns, like first class direct mail. It’s less critical for very inexpensive campaigns, such as those delivered by e-mail.

Because you’re only mailing once to each household, you have a decision to make: Who gets the letter? You can sidestep this issue by simply mailing to the Smith Family. But, such communications are more frequently discarded. Many marketers decide to flag one member of each household as the designated head of household. This is the person to whom marketing communications are addressed.

Contrary to common preconceptions, it has been fairly clear to marketers for a long time that more often than not, it is the wife, not the husband, who drives purchase decisions. For this reason, designating the eldest female as the head of household has become fairly common. Depending on your business, though, you may decide it makes more sense to communicate with a different member of the household.

Mailing just once to a household also reduces the risk of double counting responses. Say you mail multiple pieces to the same household, and the household actually makes a purchase. A common mistake is to count that purchase separately against each piece of mail that you sent to the household. In that case, you dramatically overstate the success of your campaign.

The household is important for yet another reason. You are interested in understanding your customers as well as you can. A great deal of information that is available to you from outside vendors is actually household-level information. The famous Nielson TV ratings are gathered by household. Census data is gathered at the household level. Income data is generally reported at the household level.

You may decide to purchase household-level data about your customers. If so, it’s important that you purchase data that’s relevant to your business and your situation. The accuracy of each individual piece of purchased data varies greatly according to where it comes from.

It’s a good idea to compile the best data from multiple providers based on their ability to provide quality and accuracy for your unique customer base. You can do that by providing a sample of the database to several vendors and comparing the data that they provide.

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